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用于评估两种治疗方法等效性的单侧和双侧数据合并的置信区间。

Confidence intervals for assessing equivalence of two treatments with combined unilateral and bilateral data.

作者信息

Qiu Shi-Fang, Tao Ji-Ran

机构信息

Department of Statistics, Chongqing University of Technology, Chongqing, People's Republic of China.

Department of Statistics, School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, People's Republic of China.

出版信息

J Appl Stat. 2021 Jul 7;49(13):3414-3435. doi: 10.1080/02664763.2021.1949440. eCollection 2022.

Abstract

Responses from the paired organs are generally highly correlated in bilateral studies, statistical procedures ignoring the correlation could lead to incorrect results. Note the intraclass correlation in the study of combined unilateral and bilateral outcomes; 11 confidence intervals (CIs) including 7 asymptotic CIs and 4 Bootstrap-resampling CIs for assessing the equivalence of 2 treatments are derived under Rosner's correlated binary data model. Performance is evaluated with respect to the empirical coverage probability (ECP), the empirical coverage width (ECW) and the ratio of the mesial non-coverage probability to the non-coverage probability (RMNCP) via simulation studies. Simulation results show that (i) all CIs except for the Wald CI and the bias-corrected Bootstrap percentile CI generally produce satisfactory ECPs and hence are recommended; (ii) all CIs except for the bias-corrected Bootstrap percentile CI provide preferred RMNCPs and are more symmetrical; (iii) as the measurement of the dependence increases, the ECWs of all CIs except for the score CI and the profile likelihood CI show increasing patterns that look like linear, while there is no obvious pattern on the ECPs of all CIs except for the profile likelihood CI. A data set from an otolaryngologic study is used to illustrate the proposed methods.

摘要

在双侧研究中,成对器官的反应通常高度相关,忽略这种相关性的统计程序可能会导致错误的结果。注意在单侧和双侧联合结果研究中的组内相关性;在Rosner相关二元数据模型下,推导了11个置信区间(CI),包括7个渐近CI和4个用于评估两种治疗等效性的Bootstrap重采样CI。通过模拟研究,根据经验覆盖概率(ECP)、经验覆盖宽度(ECW)以及近中未覆盖概率与未覆盖概率之比(RMNCP)来评估性能。模拟结果表明:(i)除Wald CI和偏差校正Bootstrap百分位数CI外,所有CI通常都能产生令人满意的ECP,因此推荐使用;(ii)除偏差校正Bootstrap百分位数CI外,所有CI都提供了较好的RMNCP且更对称;(iii)随着相关性测量的增加,除得分CI和轮廓似然CI外,所有CI的ECW呈线性增加趋势,而除轮廓似然CI外,所有CI的ECP没有明显模式。使用一项耳鼻喉科研究的数据集来说明所提出的方法。

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